Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/ashtonian/llm-init/data-modelnpx skills add ashtonian/llm-init --skill data-modelgit clone --depth 1 https://github.com/ashtonian/llm-initWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00011 | $0.01340 |
| Opus 5 | $0.00005 | $0.00670 |
| Sonnet 5 | $0.00002 | $0.00268 |
| Haiku 4.5 | $0.00001 | $0.00134 |
Grade A, and why
data-model scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Model Design Skill
Interactive workflow for designing database schemas, generating migrations, and creating repository interfaces for multi-tenant SaaS applications.
Workflow
Step 1: Identify Entities and Relationships
Analyze the feature requirements to identify:
- Entities: Core data objects (e.g., User, Project, Invoice)
- Relationships: One-to-one, one-to-many, many-to-many
- Aggregate roots: Which entities are accessed independently vs. through a parent?
- Value objects: Embedded data that doesn't have its own lifecycle
Output: Entity relationship diagram in Mermaid format.
erDiagram
TENANT ||--o{ USER : has
TENANT ||--o{ PROJECT : has
PROJECT ||--o{ TASK : contains
USER }o--o{ PROJECT : "member of"
Step 2: Design Tables with Multi-Tenant Columns
For each entity, design the table following .claude/rules/data-patterns.md:
Every table MUST include the base entity fields:
id(UUID, primary key)tenant_id(UUID, NOT NULL, foreign key to tenants)created_at(TIMESTAMPTZ, NOT NULL, DEFAULT now())updated_at(TIMESTAMPTZ, NOT NULL, DEFAULT now())deleted_at(TIMESTAMPTZ, nullable for soft delete)created_by(UUID, foreign key to users)updated_by(UUID, foreign key to users)
Plus entity-specific columns with proper types, constraints, and defaults.
Output: Complete table definitions with column types and constraints.
Step 3: Define Indexes and Constraints
For each table, define:
- Primary key: UUID (default gen_random_uuid())
- Foreign keys: All relationships with ON DELETE behavior
- Unique constraints: Business uniqueness rules (e.g.,
UNIQUE(tenant_id, email)) - Indexes: Foreign keys, common query patterns, search fields
- Check constraints: Enum validation, range validation
- Partial indexes: Active-only queries (
WHERE deleted_at IS NULL)
Rules:
- Every foreign key MUST have an index (Postgres doesn't auto-create them)
- Composite indexes: most selective column first
- Use
CREATE INDEX CONCURRENTLYfor large tables
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 184 lines · 11 tokens per session scan A 79e0b811b36b
data-model is a skill published in the GitHub repository ashtonian/llm-init (2 stars, last pushed 6mo ago), licensed MIT. It adds 11 tokens to every session and 1,340 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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